The present disclosure generally relates to the field of building automation systems. The present invention more particularly relates to systems and methods for classifying data points within a multi-point network based on processing the non-standard and semantically rich descriptions of the points.
Advanced building management system applications sometimes rely on the classification and identification of points. Conventional building management system commissioning processes rely heavily on manual point classification methods. In other words, a user manually evaluates an existing point and manually classifies the point under the schema or protocol for the new application.
Building automation systems are, in general, hardware and/or software systems configured to control, monitor, and manage devices in or around a building or building area. BAS subsystems or devices can include heating, ventilation, and air conditioning (HVAC) subsystems or devices, security subsystems or devices, lighting subsystems or devices, fire alerting subsystems or devices, elevator subsystems or devices, or other devices that are capable of automating or managing building functions, or any combination thereof.
Building automation communication standards such as BACnet and oBIX provide mechanisms to uniquely identify a data item or point within a domain of interest (e.g., within a system or a controller). The standards also allow description of the function of a data point. However, the standards are designed for human operators, not for machine processing. The human operators often decide upon a naming convention that roughly describes the location, type, or other attributes of the point. For example, a human operator might decide to name a power meter located at building C1, Floor 3, East as “BLDG-C1/ZONE/F-3/EAST/UTILS/EMETER/PWR-3,” where forward slash is used as a delimiter. Despite good intentions, point names are often non-standard and difficult to parse. If the goal is assigning a discovered point to a rich functional description that an application can understand and process, the commissioning process can be very lengthy for buildings having many points. For example, given 50,000 discovered points and a conservatively quick one minute per point to review, classify, and commission, over eight hundred hours of manual investigation may be necessary to configure building points such that they will be useful to an application that relies on accurate functional classification and mapping. Because not all points are necessary for an application, points that are relevant to an application must be selected. This is also accomplished through manual investigation of naming conventions, when such conventions exist. Relevant points must be mapped into the specific equipment. For example, HVAC equipment generally comprises a set of points. Temperature sensors, cooling/heating set points, humidity, discharge air temperature, and other points, for example, may be associated with a single variable air volume (VAV) box. Conventionally, spatial relationships among points, equipments and building spaces must be manually identified and mapped.
Current building automation system naming standards lack the expressive power to (1) assign a computable semantic type description to a specific point, and (2) create a relationship among building related objects (e.g., temperature sensor, fan speed, electricity consumption, zone, equipment, etc.). Even though BACnet provides an object identifier, an object name, and an object type as mandatory attributes (e.g., character strings) to describe a point, there is no extension to describe the function of the point as an object type and to define relationships among multiple BACnet objects. Human interpretation of attributes is required to identify the function of the point for further programming or application binding. Often additional programming and nonstandard metadata management are used to support new building automation system applications.
The challenges already discussed are increased by the reality that enterprise class building automation systems are often the collection of heterogeneous building automation subsystems and devices. Furthermore, over time different building engineers may add-to or otherwise modify the system. For example, to describe outdoor air temperature, one operator may use “OAT,” while another uses “Outdoor Temperature.” It is also possible for multiple languages (e.g., English and Spanish) to variously be used in naming and describing a single system configuration. The uniqueness of each language makes word extraction or word segmentation extremely challenging. For example, Chinese and Japanese do not have white space to delimit characters at word boundaries. Many European languages, e.g., German, permit free form word jointing to make compound words. There are many abbreviations to shorten the description of points, and there are many variations for each abbreviation. For example, to describe zone temperature, “ZT,” “ZN-T,” “ZNT,” and others may be used. An organization may use custom coding technology to encode data points. Such systems may be lookup based, such that a point is assigned a unique identifier, e.g., 01V001AI01.
For at least the reasons noted above, it is challenging and difficult to develop systems and methods for classifying data in building automation systems.